highlights

In a recent episode of Hello Monday, Jessi Hempel interviews Dr. Natalie Nixon on creativity and her new book, The Creativity Leap. Natalie’s PhD in Design Management—plus her work in fashion, design, and business—led her to a catchy and compelling description of creative work. We accomplish creative work, she says, “by toggling between wonder and rigour.”

In the podcast conversation, Jessi and Natalie talk about intuition—and I was struck by something. “We don’t talk about intuition,” Natalie notes at about 6 minutes in. “We don’t talk about intuition in business school, in law school, or in medical school.” And yet, she says, “I observed that really successful leaders—especially really successful startup leaders—in their origin stories, there’s always this moment where ‘Something told me not to do the deal. Something told me to work with her over him.’ […] Every successful leader really reckons with incorporating acting on their intuition to make decisions.” Jessi agrees, noting that intuition comes up often in her interviews with leaders on Hello Monday as leaders cite it as the reason for their success.

The thing is, just because we don’t name intuition doesn’t mean we aren’t talking about it. That’s because intuition is really just confident, logical thinking.

Charles Sanders Peirce was a philosopher. He investigated how we inquire into and discover new knowledge.¹ Before Peirce, we generally recognized the logical processes of deduction and induction. Deductive thinking helps us identify what must be true about a situation in order to explain it. When we deduce something, we look at the general rules and principles we know of and draw specific conclusions from that evidence. Inductive thinking involves drawing general conclusions from specific, limited evidence.

Peirce argued that effective reasoning follows a pattern: we determine the specific consequences of an idea (deduction), and then we judge whether the available evidence fits that idea and its consequences (induction). But how do we develop ideas?²

Abduction is the name of the logical process Peirce described for developing ideas. To think abductively means to generate and choose ideas that fit the situation at hand. A good idea should be verifiable—we should be able to use evidence to judge its fit—and should help us resolve the situation at hand. Peirce also had criteria to help choose the best ideas to test. He suggested that we should strive to conserve resources (e.g., those that most are most efficiently verifiable and usable in the situation), identify the most valuable ideas (specifically the “uberty” of an idea, or how likely it is that a possible idea might bring about an innovation), and the most relevant ideas (e.g., those that may apply beyond our current focus, too).³

Abduction is clearly an important step in any innovative process—but it is no more important than testing and using the ideas you generate. What, then, if you don’t have enough evidence to truly test and prove your ideas?

The process Peirce described—abduction, deduction, induction—is the ideal. However, we do not always have time and energy to follow the process diligently. Instead, we quickly make creative judgements based on a few observed qualities. This requires two related processes.⁴ The first Peirce called “abductory induction,” and it combines the first and last step of the inquiry process. We observe the qualities of the situation, and we generate possible ideas to resolve it based on those observations. The second process is known as “inference to the best explanation” (IBE).⁵ IBE is exactly what it sounds like. Given a number of possible ways of resolving a problem, choose the best one. (Peirce’s criteria, noted above, apply here.)

So what does all this have to do with intuition?

Intuition is the confident application of these shorthand logical approaches to creative problem solving. As Jessi and Natalie noted, we aren’t often explicitly taught about strengthening our intuition. Yet, everything we learn supports its development. The more we have to draw on in order to pull into the processes described above, the better our intuitive decisions will be.

I say that intuition is the confident application of these processes because they only work when we follow through. In reality, we use abductory induction and IBE all the time. When we engage in creative problem solving, we’re not only using information from the evidence in front of us. We’re drawing on our lived experience and our knowledge base. Even if we don’t directly recall or reference that background information, it is drawn into the creativity of abduction and it defines the general rules and principles we use in deduction. It provides us with the heuristics we use when engaging in IBE. But if we don’t have a bias towards action and instead operate with e.g., perfectionism, we fail to actually execute on these ideas. Thus, we need to have confidence in our abductory induction and IBE processes.

All this is simply a gentle challenge of the idea that we don’t talk about intuition. I think that all knowledge management practices and forms of education are actually fundamentally about strengthening our intuition.

That said, Natalie’s work is fascinating. I recommend the episode of Hello Monday and plan on picking up her book!

The report concludes that the campaigns represent “a clear danger to democracy” and could allow powerful organizations to target their opponents. “The extensive targeting of American nonprofits exercising their first amendment rights is exceptionally troubling,” Citizen Lab’s report says.

We didn’t want this part of cyberpunk sci-fi…

This is a quickly-sketched model created from a breakout group conversation during the MUN School of Graduate Studies’ “Earth’s Carrying Capacity” dialogue.

Download the model

According to designer/strategist Roger Martin, a strategy is an imagined possibility with which we ask the question “What has to be true for this possibility to become real?”

In this episode IDEO U’s Creative Confidence podcast, Roger talks about how that approach helped unlock Bianca Andreescu’s success at the Grand Slam singles championship in 2019.

One of the fascinating things about this approach is that it acknowledges the need for system-wide changes. By asking “What has to be true?”, a strategist must consider all of the conditions of a system that should shift to make the imagined possibility a reality. Of course, most approaches to strategy do require some appreciation of the state of the strategic environment (e.g., the five forces model). None, however, emphasize the need to guarantee these systemic conditions quite as explicitly as asking “What must be true?”

This changed with the emergence of “Patient 31.”

Reuters’ coverage of the “Korean clusters” provided the world with a vivid glimpse of the volatility of COVID-19. One person showed poor judgement, and in turn caused cascading catastrophe in her communities.

Events like the COVID-19 pandemic are thankfully rare. Moments like these—when a lot happens all at once, and the experience is shared by a collective—shape future history like nothing else. We are learning a lot from this. Not only are epidemiologists now a famous profession, but we’re all learning exactly what it takes to provide good healthcare, what good governance looks like, how public health is community health, and more.

Patient 31 holds a simple lesson for systemics: the fragility of apparently solid social systems. South Korea seemed to do everything right. Yet, due to the volatile nature of this particular socio-health system, a single “free radical” caused immense damage.

Similar volatility is evident—but more subtle—in other social systems. Consider how memes spread. Our massive communities may seem immovable at times, but it’s clear that the wrong (or right) phenomena can spread rapidly and deeply.

Stay safe.

I have often hesitated to draft up an idea because I’m not sure the folks reading this site want to hear it. I (aim to) publish about a few disparate subjects, really:

• Systemics, design, and social change
• Data modelling and data for social change
• Productivity and personal knowledge management
• Scripting and (personal) automation
• Leadership, innovation, and changemaking

Obviously, this is too many topics for any one blog. If you’re reading this, you probably came here for just one of the topics above, and you might be interested in another one or two. And listen, I like you, and I want any visit of yours to be a valuable one. That’s why I’ve launched a sibling blog.

I could cluster the topics above a number of ways. Here’s what I think makes the most sense: This blog, Fulcra, will focus on finding leverage for complex change, including:

• Systemics, design, and social change
  
• Data modelling and data for social change
  
• Leadership, innovation, and changemaking

The newest one, Axle, will focus on how we change ourselves, including:

• Personal development
  
• Design and technology for augmented cognition
  
• Productivity and personal knowledge management
  
• Scripting and (personal) automation

Moving forward, this site (Fulcra) will be a platform for writing on complex systems change. I aim to study, share, and write about how the world changes—and how we can get better at changing it.

Axle is a new site I will use to share my thoughts on how we change ourselves. After all, the better we get, the better we better get. The easy thing to write about (and what you’ll probably see the most often there) are the apps and tools I use and the designs I apply in my life and work. I also plan to share functional resources (such as scripts) as well as ask questions and debate about making progress in life and work.

This was a weird decision. After all, I barely publish here, so running two different sites seems like a terrible idea. I hope, however, that having more focused platforms for these different topics will help me publish more impulsively. Feel free to follow both, or none!

And so the Swedish gender equality initiative team began to explore whet her snow clearing was sexist. Sure enough, they found the routine of clearing snow typically benefited men over women. In the winter, snow was cleared first on main roads leading into the city, benefiting commuters—who were mostly men. Foot- and cycle-paths were cleared last—not so good for pedestrians and cyclists, who were very often women traveling with children in pushchairs.

There was a cost to all this: 79% of pedestrian injuries occurred in winter, of which 69% were women. The estimated cost of these falls was SKr36m per winter, about USD$3.7m / £3m / €3.4m / Indian ₹279m. By clearing paths first, accidents decreased by half and saved the local government money.

Great action-based response to a stupid remark (“At least snow-clearing was something those ‘gender people’ can keep their noses out of,” someone had said, prompting this investigation).

“The ISA is the business model, not education,” says Kim Crayton, a business strategist and founder of CauseAScene , an organization that’s seeking to disrupt the status quo in tech. “You cannot tell me that education is your business model when you have not registered as an institution.” For months, Crayton has been speaking about the problems with coding bootcamps on her podcast, where she’s argued that they target vulnerable communities. “You’re put in these spaces and putting in 110 percent and it’s still not working and you’re told to ‘trust the process,’” she says.

Great reporting on this at The Verge.

Kim Crayton makes an excellent point. The promise of many of these neo-credentials is for students to leapfrog the things everyone fears about the conventional education system. No one is more vulnerable to taking on loads of student debt than those who need it most. Those students are also going to suffer the most if their university or college fails to equip them for a career. Lambda solves both of these problems, making it extremely attractive to poor students.

Sadly, there’s always a catch.

Ben Thompson, in discussion with John Gruber:

It was mindblowing. It was absolutely incredible. The way that you could just do stuff that wasn’t really possible [on a computer]. Again, it was technically possible on a computer, but the user interface and experience was just transformative on the iPad. It was absolutely incredible.

And Jobs knew it. It’s one of my all-time favourites Jobs moments. It’s like fifteen seconds after the demo, and it’s just like… he’s used this. He was involved in the creation of it. They had run through the demo. He knew it. And even then, he was just astonished. He’s just like ‘I can’t believe [this]…’

[…]

It was, to my mind, the culmination of his life’s work. He comes on there, and he’s like, ‘Isn’t it incredible? Now anyone can make music.’

I almost want to transcribe this whole episode. John Gruber and Ben Thompson discuss the potential of the iPad—and its failure to reach it.

Ben uses the term “transformative” deliberately above. They discuss how, before the iPad, no computing experience could adapt to become wholly new tools and environments for whatever the user wanted to do. But the iPad can become a piano or a canvas or a television. In this sense, they argue that the iPad has (or had) the potential for disruptive innovation (RIP Clay Christensen)—but it’s not supposed to be a Mac.

These two think the iPad’s lost the chance to fulfill that potential, mostly because Apple has missed the opportunity to build a vibrant developer ecosystem due to App Store policies. I hope that isn’t the case, though I think we have to look beyond the iPad to fully appreciate what might happen next. The introduction of tablets and transformative computing experiences continues to echo throughout a variety of industries. Graphic designers and illustrators have a new suite of tools to directly interact with their creations in the iPad Pro and the Surface. Similarly, tablet or hybrid devices have transformed schools—schoolchildren now have a “homework” device for all kinds of assignments. It’s true that we still need developers to imagine ever-more revolutionary applications for these devices, but there’s no denying that disruption is taking root.

Either way, the episode is well worth a listen. Enjoy from 15:50 to ~31:22 and 1:26:59 to the end of the show if you want to focus on the iPad discussion.

My bank, fitness and workout apps, and food delivery services I haven’t used in months—those were some of the 30+ apps interacting with Facebook data. Ostensibly this data is used to personalize ads.

As of today, our Off-Facebook Activity tool is available to people on Facebook around the world. Other businesses send us information about your activity on their sites and we use that information to show you ads that are relevant to you. Now you can see a summary of that information and clear it from your account if you want to.

Off-Facebook Activity marks a new level of transparency and control. We’ve been working on this for a while because we had to rebuild some of our systems to make this possible.

Now, thankfully, you can review these connections yourself and clear any history manually. Check out Facebook’s Off-Facebook Activity controls, and happy Data Privacy Day.

If the product is free, you are the product:

An antivirus program used by hundreds of millions of people around the world is selling highly sensitive web browsing data to many of the world’s biggest companies.

In what appears to be something of a purposeful dark pattern, the only thing differentiating ads and search results is a small black-and-white “Ad” icon next to the former.

Hrm. The resulting change seems to work:

Early data collected by Digiday suggests that the changes may already be causing people to click on more ads. […] According to one digital marketing agency, click- through rates have already increased for some search ads on desktop, and mobile click- through rates for some of its clients increased last year from 17 to 18 percent after similar changes to Googleʼs mobile search layout.

Damn. I may start looking for a new search engine.

[People] tend to ignore outside forces and focus on each other. This comes naturally. They believe they are responsible for everything because they believe they have no limits to the mastery of their fates, a false belief but their central motivation, perhaps good for their mental health, since powerlessness is hopelessness.

If you haven’t heard of Sue Burke’s “Pax” duology, and you like sci-fi, I’m happy to recommend a new favourite book series for you.

The Pax books are about a rebellious attempt to save humanity in which several families build their own ship and escape to a new planet to begin a new colony. Doing that is about as straightforward as it sounds. Sue Burke brings this premise to life masterfully.

The most audacious commitment from Microsoft is its push to take carbon out of the atmosphere. The company is putting its faith in nascent technology, and it’s injecting a significant investment into a still controversial climate solution. Proponents of carbon capture, like Friedmann, say that the technology is mature enough to accomplish Microsoft’s aims. It’s just way too expensive right now. Microsoft’s backing — and its $1 billion infusion of cash — could ultimately make the tech cheaper and more appealing to other companies looking for new ways to go green.

Fantastic news. Carbon capture is a key opportunity for decelerating climate change. Hopefully more companies follow suit.

A surprising headline, but the restriction is very specific:

the new export ban is extremely narrow. It applies only to software that uses neural networks (a key component in machine learning) to discover “points of interest” in geospatial imagery; things like houses or vehicles. The ruling, posted by the Bureau of Industry and Security, notes that the restriction only applies to software with a graphical user interface — a feature that makes programs easier for non- technical users to operate.

Still, this is probably a marker of change to come. It’s a little odd to think of software as something that can be “exported”, however. Surely this isn’t a ban on shipping discs across a border. Software is downloaded. So, is this a kind of firewall?

Dr. Ngumbi and Dr. Lovett outline the issues with modern research conferences that are stuck in the 20th (or even 19th) century.

By the end of each conference, you’ve heard dozens of people dispense all their knowledge in 10-minute bursts, and you sometimes leave feeling less informed than before you arrived. Where’s the dialog? Where’s the questioning? Where’s the innovation? It’s beyond time that scientific conferences themselves undergo the scientific process, and move forward.

I shouldn’t ever be surprised by these events, but every time I go to one, I am shocked by how boring the facilitation is. Some might defend the format. After all, sage-on-a-stage has worked for hundreds of years.

The question isn’t whether it works, though. It’s whether it could be better. Surely, in an age of cloud technologies and the Internet and social media—not to mention better recognition of soft power and inclusivity and the processes of scientific revolution—there are modes of conference programming that can leapfrog the conventional format.

Having led a number of events over the years that have shirked tradition for more interesting facilitation formats, I know firsthand how disruptive facilitation mistakes can be. But I’ve also seen some incredible results from shaking up the structure. Radhoc’s Unpanel, for instance, turns the structure of a panel upside-down. Instead of having a group of “experts” on a stage speaking to an anonymous crowd, the format puts those invited guests in subgroups that get to introduce one another. The audience becomes the panel, and the expert an anchor in the conversation. It gives everyone a chance to connect with the quasi-celebrities anointed by these events. As a bonus, it’s easier for the guests, too—they don’t need to prepare keynotes, only business cards.

Bohn and his co-founders are confident that, if done right, a proper system for wireless power transmission could shift not just how we think about keeping devices charged and powered on at all times, but also the types of devices we end up putting in our homes and what those devices get used for.

I’d say. If this works, it’ll remove a technical limitation that is pretty built-in to our mental models of how our gadgets work.

Guru is envisioning a world where you can keep all manner of battery-powered gadgets, big and small, all over your home or in every corner of an office, store, or warehouse without having to worry about where they draw power from or how long it lasts on a charge.

Eliminating the “where will I plug it in?” assumption might unlock opportunities across all ways of living and working.

Segwayʼs newest self-balancing vehicle wonʼt require you to stand up. Dubbed the S- Pod, the new egg- shaped two-wheeler from Segway-Ninebot is meant to let people sit while they effortlessly cruise around campuses, theme parks, airports, and maybe even cities.

Hmm. At least with self-balancing, this won’t happen.

From @jack himself:

Twitter is funding a small independent team of up to five open source architects, engineers, and designers to develop an open and decentralized standard for social media. The goal is for Twitter to ultimately be a client of this standard. 🧵

The thread is worth the read, as are some of the comments. There’s a few interesting resources shared within, including a couple of articles from Jack and a few existing open standards.

Every part of this trial sounds made up. They should just air it in lieu of a Good Fight episode. Elizabeth Lopatto’s writeup is worth worshipping.

Spiro then coined the worst acronym I’ve heard in years, and I edit stories about aerospace so I know from bad acronyms. It is: JDART, for joking, deleted, apologized-for, responsive tweets.

Incredible.

But there’s at least one abstract takeaway that’s interesting to me:

At this point, Wood tried to enter an email exchange into evidence, resulting in a great deal of confusion on Judge Wilson’s part about how email reply chains work. (You read from the bottom.)

[…]

At this point, the “pedo guy” Twitter thread was entered into evidence, and the befuddled court had to be told that the reply chains work the other way on Twitter — the first tweet is at the top, and the last tweet is at the bottom.

Yet another example of the ways in which the world’s accelerating faster than many institutions can keep up.

Anyone, anywhere can propose an idea. YouTube creators will help spread the word, and the best proposals could be put into motion with the help of businesses, policymakers, and and celebrities supporting the initiative.

The initiative will culminate in a summit in Bergen, Norway next October to share the solutions that came out of the effort. Countdown will work with a panel of experts and scientists to vet proposals, and the strongest will be turned into TED talks. The talks will be filmed at the summit in Norway, in front of “a hand-picked audience capable of turning those ideas into action,” according to a press release.

An interesting partnership, and yet another example of “crowdsolving”: trying to find solutions to wicked problems via the mobilizing power of the Internet.

I certainly expect to see some concepts from Drawdown on stage.

In this research article, the authors point out that the cycles of translation from English to the language of the context and back again can be costly and inconvenient. But, they point out three benefits to investing in translation and multi-lingual research spaces.

First, the authors argue that disseminating the results of research in local languages not only makes your research accessible to stakeholders, but it also helps stakeholders value all research more. They write:

Translations are expensive and time-consuming, so a large part of our work stays in English unavailable to the local stakeholders, who may have participated in the research process. This is an issue not only because it reduces their possibilities to learn from the systematized outcomes of the processes in which they participate, but because it reduces their perception of the value of research. When stakeholders feel that researchers write exclusively for other foreign researchers, their readiness to support and fund research may decrease.

The second benefit:

Second, academics who don’t read English may find it difficult to continue building on knowledge published only in that language.

This takeaway is obvious. So many publications are translated to English, but the reverse is rare.

Third, and by no means least, naming complex issues or ideas only in English impoverishes other languages. When we forsake finding a word for a particular concept or idea in a given language, we impoverish that language.

This is quite insightful. Language is intrinsic to organizational learning. If the concepts advanced in our research are never introduced to the local language, then it may be impossible for that learning to take root.

The authors recognize a fascinating tension in this work. They demonstrated the possibility of multi-language research spaces via a virtual research commons for their project.

What we have learned from working with different languages and acknowledging them during the full research cycle, including the dissemination stage, is that they are time- consuming, costly and even a bit messy and uncomfortable. For example, in the case of the virtual space above, some participants complained that having to find their own language among texts written in other languages begs an extra effort from them and slows them down. However, the alternative is renouncing inclusion and plurality, which is at odds with the challenge faced by academia to address complex societal problems.

There is a cost to complexity, but solution spaces need to be more complex than the problems they’re resolving.¹

Chinaʼs 2017 decision to turn away Americaʼs trash has left the recycling industry reeling as it figures out what to do with all the packaging online shoppers leave behind.

Recycling is a funny thing. For me, it’s almost a guilt-free act. “Sure, I’m using all of these boxes, but they’re recycled, so who cares?” But increasingly recycling and the trash bin seem like equivalent destinations. It’s even imaginable that recycling is worse, because recycled objects might travel farther before being dumped into a landfill anyway.

“Itʼs very difficult for American material recovery facilities to satisfy that standard because Americans put plastic bags and chewing gum and bowling balls and dirty diapers and everything else you can imagine into the recycling containers,” Biderman says. The strict rules also apply to plastic and other recyclables, but cardboard and mixed paper have seen the sharpest drops in prices.

I’m tempted to blame people: “It’s too bad we can’t be more considerate. Have you ever looked in the recycling bins in public receptacles?” Et cetera. But really, we should be designing systems that make this easy—or incentivize good behaviours somehow. Either way, the current situation is insufficient:

There has also been a noticeable shift in the source of the cardboard, says Coupland: itʼs coming from peoplesʼ homes instead of brick-and-mortar businesses. Thatʼs bad news, since retailers are less likely to generate cardboard thatʼs too filthy to be recycled. Consumersʼ cardboard boxes are often mixed with other, dirty recyclables like ketchup bottles or soda cans that spill their contents over the cardboard. On average, about 25 to 30 percent of the materials picked up by a recycling truck are too contaminated to go anywhere but a landfill or incinerator, Coupland says.

Today former Secretary of State John Kerry and former California governor Arnold Schwarzenegger declared war on climate change. The two led an all-star cast of lawmakers and celebrities to launch an initiative called World War Zero, which aims to get individuals, businesses, and governments to drastically slash greenhouse gas emissions. The initiative, for now, boasts a lot of glitzy names without many details on how it will achieve its goal. Its bipartisan founding members — which include Bill and Hillary Clinton, Richard Branson, Jimmy Fallon, Cindy McCain, and Al Sharpton, and more than 70 other notable names — plan to hold 10 million “climate conversations” in 2020, The New York Times reported over the weekend.

Seems like an incredible effort. And it’s an excellent angle. “War”—when declared by major public figures—certainly catches the public attention.

Kerry compared the urgency of climate change to the challenges facing America during World War II. “When America was attacked in World War II we set aside our differences, united and mobilized to face down our common enemy,” Kerry said in a statement. “We are launching World War Zero to bring that spirit of unity, common purpose, and urgency back to the world today to fight the great threat of our time.”

Of course, actually waging war doesn’t always garner the unity or have the results we aim for, especially when it’s a war against a social issue.

Existing options for algorithmic evaluation of the similarity of documents depend on shallow measures: does this word seem important? What words is it used with? How frequent are they? Which is why this is cool—in this paper, the authors compare the language in a given document with broader knowledge of words and their synonyms:

In this paper, the Frequency Google Tri-gram Measure is proposed to assess similarity between documents based on the frequencies of terms in the compared documents as well as the Google n-gram corpus as an additional semantic similarity source.

And it works!

The experimental results demonstrate that the proposed measure improves significantly the quality of document clustering, based on statistical tests. We further demonstrate that clustering results combining bag-of-words and semantic similarity are superior to those obtained with either approach independently

Scary:

One issue identified on an unnamed carrierʼs implementation could allow any app on your phone to download your RCS configuration file, for example, giving the app your username and password and allowing it to access all your voice calls and text messages. In another case, the six-digit code a carrier uses to verify a userʼs identity was vulnerable to being guessed through brute force by a third-party. These problems were found after researchers analyzed a sample of SIM cards from several different carriers.

RCS is supposed to be a big deal. It’s fascinating how these system-wide policies can be messed up in microsystem implementations.

This report is intentionally broad and robust. We have included a list of adjacent uncertainties, a detailed analysis of 315 tech trends, a collection of weak signals for 2020, and more than four dozen scenarios describing plausible near futures.

Impressive work. I particularly like the CIPHER heuristic they use in analysis signals: contradictions, infections, practices, hacks, extremes, rarities.

Medical crowdsourcing offers hope to patients who suffer from complex health conditions that are difficult to diagnose. Such crowdsourcing platforms empower patients to harness the “wisdom of the crowd” by providing access to a vast pool of diverse medical knowledge.

An interesting application of crowdsourcing. What’s the incentive for healthcare providers to participate, though? I’m not sure doctors can bill for participation in Figure 1. I think the main reason they engage at all is curiosity, and that would likely degrade if, as the authors of the linked study discuss, there was a lot of “noise” from uninteresting posts by patients who aren’t medically literate.

Today, we’re excited to formally launch the final version of OPSI’s AI primer: Hello, World: Artificial Intelligence and its Use in the Public Sector

Another interesting output from the OPSI. It seems usefully pragmatic:

The AI primer is broken up into four chapters that seek to achieve three key aims: (1) Background and technical explainer; (2) overview of the public sector landscape; (3) implications and guidance for governments.

We find that high-, medium-, and low-engagement-state gamers respond differently to motivations, such as feelings of effectance and need for challenge. In the second stage, we use the results from the first stage to develop a matching algorithm that learns (infers) the gamer’s current engagement state “on the fly” and exploits that learning to match the gamer to a round to maximize game-play. Our algorithm increases gamer game-play volume and frequency by 4%–8% conservatively, leading to economically significant revenue gains for the company.

As ever with this kind of mechanism, are we sure we want this to exist..? The potential is no doubt powerful. Imagine interactive TV shows that modulate what they’re presenting based on readings of the viewer… Hrm.

The halo effect is essentially how positive—but irrelevant—traits influence our perception of what the thing with the halo actually says or does. These authors explored how charities manifest the halo effect on their websites, and find evidence for four varieties of halo effect.

this study employs charity websites as a multi-attribute donation channel consisting of three attributes of information content quality (mission information, financial information, and donation information) and four attributes of system quality (navigability, download speed, visual aesthetics, and security). Based on the proposed framework, this study proposes four types of halos that are relevant to charity website evaluation —collective halo (attribute-to-attribute), aesthetics halo (attribute-to- dimension), reciprocal-quality halo (dimension-to-dimension), and quality halo (dimension-to-dimension)

This is a great talk from Piret Tönurist of the Observatory on Public Sector Innovation.

One of the core issues of the talk is innovation doubt—the “if it ain’t broke, don’t fix it” mentality. To paraphrase Piret:

[…] why are we doing innovation at all? Maybe sometimes things are working fine, why do we think about innovation at all? We start off with four questions:

1. Do you want to do things better?
2. Do you have goals and purposes to fulfill?
3. Do you want to address the needs of your stakeholders?
4. Do you want to prepare for the risks and uncertainties that the future holds? If you answered “yes” to at least one of those questions, then your job is to do innovation—your job is to be a changemaker.

Also, the talk includes a neat model for different varieties of innovation, image courtesy of this post by Adrian M. Senn over on Medium:

I came across this talk via a related panel discussion.

In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of Artificial Intelligence (AI) and intelligent automation.

cf. Lee Se-Dol.

This is according to the latest IBM Institute for Business Value (IBV) study, titled The Enterprise Guide to Closing the Skills Gap.

Seems like an interesting guide. This metric surprised me:

In 2014, it took three days on average to close a capability gap through training in the enterprise. In 2018, it took 36 days.

I didn’t know this measure existed, but I can see the utility. As knowledge work grows ever more specialized, this time-to-capability can only grow.

In two senses, the work of innovation for public value and social impact is changing in Australia and around the world. What we expect public innovation to do and what we need it to achieve, and how that work should be done, are both changing. And they are changing together while they are changing each other.

It’s true. It’s hard to keep up with the discipline of changemaking, but it’s even harder to keep up with the change that needs to be made. Therefore Martin Stewart-Weeks calls for optimism:

Despite some of the uncomfortable and unsettled conditions, there is real energy in the search for more effective ways to solve the big problems we face in common — managing our complex cities, rewiring large and complex health and social care systems, tackling climate change, searching for better ways to integrate the human and technology capabilities of the digital age and making our communities healthy and resilient.

The speed, intensity and sheer connectedness of these and many other complex, public challenges are giving rise to new methods and tools that can help to tackle them with purpose and skill.

The South Korean Go champion Lee Se-dol has retired from professional play, telling Yonhap news agency that his decision was motivated by the ascendancy of AI. “With the debut of AI in Go games, Iʼve realized that Iʼm not at the top even if I become the number one through frantic efforts,” Lee told Yonhap. “Even if I become the number one, there is an entity that cannot be defeated.”

Wow. Perhaps the first real example of “AI took my job?”

The Twttr prototype app gave me another feedback form today. It’s been my habit to complain, at every opportunity, about the trends page you have to engage with whenever you go to the Search tab. I feel a little bad for the designers and developers, because the beta is really all about how conversations on Twitter look and feel. Still, this feedback form was no different. Here’s what I wrote in the “Dislike” section:  I wish I could control the trends page.

It is the absolute worst part of my Twitter experience. It just feels… unhealthy. Like going through a grocery store magazine aisle. Sure, some of the headings are instructive or inspiring, but many are gross, irrelevant, or completely malignant gossip.

The experience is also invasive. Because trends are forced upon you when you intend on searching for something specific, and because they’re algorithmically-tunes to be as attention grabbing as possible, it’s easy to be distracted and forget why you even entered the search pane. I never explicitly consent to learning about celebrity gossip or US politics when I use Twitter. If I tap on some of those topics, it’s not because I want to. It’s because it’s malicious click bait. In turn, it’s corrupt to design an experience that drags the user through it repeatedly.

Sure, this content is viral. But shouldn’t we be inoculating against viruses, not encouraging them to spread?

An incredible story out of New York today, as reported by The Verge:

A flooded subway entrance stopped Brooklyn commuters in their tracks yesterday. For four hours on Wednesday, the staircase leading down to Broadway Station in Williamsburg was blocked off and completely submerged. The sight was even stranger since it hadnʼt rained in New York City that day.

The Transit Authority was testing adaptations they’d installed in case of real flooding. Still, I’m sure that the social/informational impact was felt, too.

Also, the MTA’s sarcastic explanation is gold. From Twitter:

We’re pivoting to submarines. ^JLP

I have a foreboding of an America in my children’s or grandchildren’s time—when the United States is a service and information economy; when nearly all the manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness…

Carl Sagan, as quoted by @Andromeda321 in this interesting Reddit thread on the regretful trends of the 2010s.

The thread discusses the growth of anti-intellectualism and conspiracy theories. I’m reminded of this timeless Medium post about how hating Ross in Friends became a meme in and of itself, reinforcing the persecution of science in the ’90s. From David Hopkins:

I want to discuss a popular TV show my wife and I have been binge-watching on Netflix. It’s the story of a family man, a man of science, a genius who fell in with the wrong crowd. He slowly descends into madness and desperation, led by his own egotism. With one mishap after another, he becomes a monster. I’m talking, of course, about Friends and its tragic hero, Ross Geller.

[…]

If you remember the 1990s and early 2000s, and you lived near a television set, then you remember Friends. Friends was the Thursday night primetime, “must-see-TV” event that featured the most likable ensemble ever assembled by a casting agent: all young, all middle class, all white, all straight, all attractive (but approachable), all morally and politically bland, and all equipped with easily digestible personas. Joey is the goofball. Chandler is the sarcastic one. Monica is obsessive-compulsive. Phoebe is the hippie. Rachel, hell, I don’t know, Rachel likes to shop. Then there was Ross. Ross was the intellectual and the romantic.

Eventually, the Friends audience — roughly 52.5 million people — turned on Ross. But the characters of the show were pitted against him from the beginning (consider episode 1, when Joey says of Ross: “This guy says hello, I wanna kill myself.”) In fact, any time Ross would say anything — about his interests, his studies, his ideas — whenever he was mid-sentence, one of his “friends” was sure to groan and say how boring Ross was, how stupid it is to be smart, and that nobody cares. Cue the laughter of the live studio audience. This gag went on, pretty much every episode, for 10 seasons. Can you blame Ross for going crazy?

People in the Reddit thread point out that these seemingly recent trends have been taking root for a long time. While this is true, it’s also true that (just like seemingly everything else) these phenomena have been moving much faster and growing much larger in recent years. Which leads to a curious tangent: how do accelerated scales of change play on our biases? Does the interaction between these biases and our accelerated experiences change our perception of the world?

The over- and misuse of AI is one of my biggest tech pet peeves. It truly is evil to tack the AI term onto the description of most products. It also damages the long-term potential of AI by corrupting what it means—especially for the everyday people who aren’t involved or invested in building these tools, but who will use them (or be used by them).

Arvind Narayanan on Twitter:

Much of what’s being sold as “AI” today is snake oil. It does not and cannot work. In a talk at MIT yesterday, I described why this happening, how we can recognize flawed AI claims, and push back. Here are my annotated slides: https://www.cs.princeton.edu/~arvindn/talks/MIT-STS-AI-snakeoil.pdf

Key point #1: AI is an umbrella term for a set of loosely related technologies. Some of those technologies have made genuine, remarkable, and widely-publicized progress recently. But companies exploit public confusion by slapping the “AI” label on whatever they’re selling.

Key point #2: Many dubious applications of AI involve predicting social outcomes: who will succeed at a job, which kids will drop out, etc. We can’t predict the future — that should be common sense. But we seem to have decided to suspend common sense when “AI” is involved.

Key point #3: transparent, manual scoring rules for risk prediction can be a good thing! Traffic violators get points on their licenses and those who accumulate too many points are deemed too risky to drive. In contrast, using “AI” to suspend people’s licenses would be dystopian.

Check out the whole thread.

If academia ceases to have an impact it loses its raison d’être. Impact is what differentiates meaningful academic work from mere busywork. It makes the difference between signal and noise.

[…]

Ultimately, the questions that concerns us [are] what role research plays in society and how we can create a research system with impact at its core?

Indeed. We have to be asking (and answering!) questions that matter.

I like this project. Benedikt and Sascha say they’re taking a systemic approach to model the full complexity of academic impact:

academia struggles with creating/measuring/generating impact because it struggles to conceptualise and structurally anticipate it. We are missing a systemic perspective on impact that is grounded in the fact that different forms of meaningful academic work show very different forms of impact.

The work is supposedly semi-open. The authors ask anyone that reads each chapter, released incrementally on Google Docs, to contribute comments, and then they will work to incorporate these insights back into the final output.

Here’s a link to the first chapter.

Abhijit Banerjee and Esther Duflo of M.I.T. and Michael Kremer of Harvard have devoted more than 20 years of economic research to developing new ways to study — and help — the world’s poor. On Monday, their experimental approach to alleviating poverty won them the 2019 Nobel Memorial Prize in Economic Sciences. Dr. Duflo, 46, is the youngest economics laureate ever and the second woman to receive the prize in its half-century history.

Amazing news. Esther Duflo has been a research-hero of mine since Cal Newport profiled her as a story of purpose-finding.

In this Wired article, Adam Savage provides a pragmatic description of how he breaks down complex projects using lists.

In my mind, a list is how I describe and understand the mass of a project, its overall size and the weight that it displaces in the world, but the checkbox can also describe the project’s momentum. And momentum is key to finishing anything.

Momentum isn’t just physical, though. It’s mental, and for me it’s also emotional. I gain so much energy from staring at a bunch of colored-in checkboxes on the left side of a list, that I’ve been known to add things I’ve already done to a list, just to have more checkboxes that are dark than are empty. That sense of forward progress keeps me enthusiastically plugging away at rudimentary, monotonous tasks as well as huge projects that seem like they might never end.

I love the physics metaphor here. There’s lots of other insights to be gained by thinking about how work follows physical principles. For instance, projects also have inertia, friction, and surface area:

1. Inertia. The longer a project sits waiting for you—weighing on your mind—the harder it is to get it moving.
2. Friction. Inertia is driven by initial friction. In parallel, of course, kinetic friction can make it hard to stop working on something. This is why multitasking doesn’t make sense with most projects.
3. Surface area: It can be hard to attack a single, huge project idea, just like how a large ice cube melts slower than many little ones. List making is a key way of breaking up the surface of a project into smaller pieces, making it easier to handle. Increasing surface area also facilitates collaboration: it’s easier to hand off smaller pieces to others, and to put them back together again.

To return to momentum, though, Adam makes an excellent point: breaking down the work helps keep momentum going even when you put the work down.

That may be the greatest attribute of checkboxes and list making, in fact, because there are going to be easy projects and hard projects. With every project, there are going to be easy days and hard days. Every day, there are going to be problems that seem to solve themselves and problems that kick your ass down the stairs and take your lunch money. Progressing as a maker means always pushing yourself through those momentum-killers. A well-made list can be the wedge you need to get the ball rolling, and checkboxes are the footholds that give you the traction you need to keep pushing that ball, and to build momentum toward the finish.

Another point in the article that’s worth emphasizing:

[I]n a project with any amount of complexity, the early stages won’t look at all like the later stages, and [the manager] wanted to take the pressure off any members of the group who may have thought that quality was the goal in the early stages.

I’ve heard this discussed in the context of critique, or “10% feedback”. When sharing work with others, it’s important to disclose the stage the work is at. Typos should be caught at a project that’s basically ready to publish. They shouldn’t even be discussed when a work is being conceptualized. The focus on early stages should be the concepts themselves, and how they fit within the broader context.

Last thing. This is excellent:

There is a famous Haitian proverb about overcoming obstacles: Beyond mountains, more mountains.

🏔

For serious system mapping work, spending [significant] time studying, thinking about, and mapping your system helps ensure you are addressing root causes rather than instituting quick fixes. In the long term, the time and resources you invest in Systems Practice will pay dividends.

But what if youʼre not quite sold on the Systems Practice methodology yet? What if you havenʼt encountered systems thinking before and just want to dip your toes in? Or what if youʼre an expert or an educator with only a few hours to introduce Systems Practice to a fresh new group of systems thinkers?

I have been in the latter situation, and it’s a challenge. In my experience, people who are wholly new to systems thinking can take a lot of time to acclimate to the mindset. But! If, as a teacher, you can’t illustrate the benefits quickly, it’s easy to disengage.

So, I’m glad this exists. This is a wonderful new resource from Kumu’s Alex Vipond that helps walk you through systems and Kumu’s tools at the same time.

Land that became too toxic for people to farm and live on after the 2011 meltdown at the Fukushima Dai-ichi Nuclear Power Station will soon be dotted with windmills and solar panels.

The Fukushima disaster unfolded as an incredible story of systemic response to new scales of tragedy. Take, for instance, the Skilled Veterans Corps: a group of elderly volunteers who helped with cleanup, knowing that the damaging radiation would have less impact on their lives than it would on younger volunteers.

Now Fukushima’s next chapter is evolving as an example of systemic creative destruction, as new opportunities are unlocked by the collapse of the region’s previous energy strategy.

“In the five years that weʼve had to asses the effect [the Gigafactory has] had on the workforce, on the community, I think there have been these ramifications that we talk about in the episode that nobody was really prepared for,” Damon said in an interview with The Verge. “Like, we knew there was going to be an issue with housing, which other cities are experiencing, too. But thatʼs become super critical.”

Side-effects of growth are not a new problem, but the massive initiatives we’re seeing recently might spark new varieties of old issues.

Through model-based learning, students use diagrams as a way to think about and reason with systems—and to think about how complex systems interact and change.

“Model-based learning” seems like a reframing of classic teaching practices, but it’s nonetheless a powerful reframing. Emphasizing the model—and encourage students to test and iterate their models—is catchy. It’s also deliberately organizational—it requires students to organize and structure their thinking about a given system, often visually.

There is a significant gap in research about Canadian data collection activities on a granular scale. This lack of knowledge regarding data collection practices within Canada hinders the ability of policymakers, civil society organizations, and the private sector to respond appropriately to the challenges and harness unrealized benefits.

So true. This looks like an interesting series from the great team at Brookfield.

Something strange is happening with text messages in the US right now. Overnight, a multitude of people received text messages that appear to have originally been sent on or around Valentine’s Day 2019. These people never received the text messages in the first place; the people who sent the messages had no idea that they had never been received, and they did nothing to attempt to resend them overnight.

It is incredible to think that this could happen on a scale big enough to hit headlines now, but it wasn’t noticeable on Valentine’s Day originally.

That’s one of the problems with our ever-more-complex technologies. We’re accommodating to the bugs. It gets easier and easier to dismiss weird tech events as glitches and move on without worrying. Unreliability is, itself, unreliable.

But there can be major consequences to seemingly innocent bugs:

… one person said they received a message from an ex-boyfriend who had died; another received messages from a best friend who is now dead. “It was a punch in the gut. Honestly I thought I was dreaming and for a second I thought she was still here,” said one person, who goes by KuribHoe on Twitter, who received the message from their best friend who had died. “The last few months haven’t been easy and just when I thought I was getting some type of closure this just ripped open a new hole.”

Herein, then, lies the tyranny of classification: The borders we draw for ourselves create a prison of thought and collaboration, inhibiting movement, connectivity, and learning.

Dominic Hofstetter outlines the many benefits of categorization, too. We have to have both specialization and generalization—categories and loose files. The key is developing processes, protocols, and ways of working that elevate the benefits of both.

The ever-refreshing Paul Jarvis shares some uncommon thoughts on productivity in Jocelyn K. Glei’s Hurry Slowly podcast.

In particular, Paul and Jocelyn discuss the importance of resilience. Citing research and his own experience, Paul points out that resilience is a more important factor in success than many others.

Obviously, though, enabling resilience is not as easy as simply pointing out how important it is. As they discuss, resilience isn’t something innate—which means that it can only be developed through experience. And this is where things get tricky: who gets to have resilience-building experiences?

In my research on innovation skills, I discovered that resilience was one of three key domains that wasn’t an important outcome for our public education systems. This means that resilience training isn’t necessarily a public good. Only if you’re lucky (or privileged) will you have the chance to build up your resilience muscle.

Incredible achievement, but it makes me wonder—what are the .2% of humans doing differently?

These stories of AI achievement are sure to proliferate in the coming years. By focusing on those people who are still able to think around machine learning strategies, we might learn something about how humans and machines can best complement each other.

From the Future Today Institute’s recent release.

The bias-on-capture issue is a particularly nuanced problem. How can we know if the capta is corrupt? Scrutiny of the capture source, perhaps?

How do you handle life’s inputs and prioritizing?

Just shared some thoughts on dealing with infinite content on Mac Power Users’ forums.

what are the scaling challenges tech companies have that do relate to post-secondary? Here’s the key quote:

“More assets than STEM skills are required for productivity growth. Additional skills such as business and management such as customer-facing skills (i.e. skills and marketing); higher order cognitive skills such as creative problem solving and critical thinking…there is a mismatch between what companies need and what local labour markets can offer. In particular, Canada is lacking a supply of business management or customer-facing talent, such as sales and marketing.”

https://medium.com/@pixelthing/fe-webdev-on-ipad-pro-2018-c55283f01e4c

Well put. Some file organizing difficulties are so obtuse that I wonder if developers use their own apps.

What struck me was the language Zuckerberg used to discuss this issue — it’s different than anything he has said before. And it goes to the heart of social networks’ role in creating a polarized, destabilized electorate:

One of the biggest issues social networks face is that, when left unchecked, people will engage disproportionately with more sensationalist and provocative content. This is not a new phenomenon. It is widespread on cable news today and has been a staple of tabloids for more than a century. At scale it can undermine the quality of public discourse and lead to polarization. In our case, it can also degrade the quality of our services.
Our research suggests that no matter where we draw the lines for what is allowed, as a piece of content gets close to that line, people will engage with it more on average — even when they tell us afterwards they don’t like the content.

our review identifies several approaches that show some promise for improving the use of research in population health policy. They include the following:

A system for commissioning rapid reviews
Tailored approaches to presenting research findings to policymakers
The involvement of policymakers in research teams and networks
Interactive seminars and conferencing technology for communicating evidence
Initiatives to build capability in people and across organisations
Funded institutional-level collaborations.

Spanning all five schools at MIT, IDSS embraces the collision and synthesis of ideas and methods from analytical disciplines including statistics, data science, information theory and inference, systems and control theory, optimization, economics, human and social behavior, and network science.

The mission of IDSS is to advance education and research in state-of-the-art analytical methods and to apply these methods to address complex societal challenges in a diverse set of areas such as finance, energy systems, urbanization, social networks, and health.

IDSS comprises a number of academic programs, including those offered by the Statistics and Data Science Center (SDSC), two online education programs, and the IDSS research entities Laboratory for Information and Decision Systems (LIDS) and Sociotechnical Systems Research Center (SSRC).

By now, it should be easy to see how different questions about your data can lead to different visualization types. This accomplishes a few things:

A question can give you a place to start when presented with a dataset, which can lead to more questions.
It provides focus, because a graphic is made to answer something specific.
Filters out what you do not need to show.

For the sake of illustration, I will highlight a possible combination of social and policy labs, transformative scenario planning, deliberative polling, civic tech, and creativity techniques that together increase impact, convergence between stakeholders, and public acceptance of outcomes.
Imagine that, as a government official, you are required to define the policy and regulatory reforms required to address an issue with system-wide implications, complex ethical dilemmas, and long-term impacts (all characteristics that our current governance mechanisms struggle with). This challenge could be the transformation of healthcare through the digital and genomics revolutions, the repercussions on our economies and societies of autonomous vehicles, or the impact on jobs of artificial intelligence. We would recommend that someone in this position follow this sequence of actions:

You partner with other government departments to design a process, ensure their buy-in, and secure initial funding.
You then bring together 30-40 key players from industry, civil society, academia, and public administration with relevant expertise, the ability to act, and diverging viewpoints. You may want to leverage this diversity of perspectives to enroll additional funding. You ask this group to agree on the three or four likely scenarios for your issue for the medium term, that is, where it will be in 10-20 years, depending on the investment and regulatory choices that could be made today. They will not agree on what scenario they would like to see emerge, but they’ll concur that these three or four scenarios are highly plausible if certain decisions are made. Reos Partners has pioneered this approach with policy labs and Transformative Scenario Planning (TSP).
You then bring together a representative group of citizens to examine the 3-4 possible scenarios. Using the deliberative polling methodology, you survey the participants for their “top-of-the-head” opinion on the topic before bringing them together to thoroughly examine the different scenarios. In the process, you elicit what scenario they favor, taking into account the options, trade-offs, and ethical dilemmas.
You may then want to leverage the diversity of views present to conduct ideation sessions for possible new policy/regulatory approaches to overcome some of the trade-offs the group identified.
At this point, you have convergence among the relevant stakeholders around the potential options, a rich set of data from citizens showing the direction of their preference, and practical ideas for implementing the vision that’s emerging. In this way, the approach provides a rich and practical template for more creative, effective, efficient, and timely policy-making.

Throughout the process, you can involve a wider set of players and citizens online, integrating their input with in-person discussions. Such an approach thus combines the breadth of perspectives that a variety of citizens and stakeholders bring (you can use deliberative polling and civic tech tools here), while allowing for the depth of expertise needed to ground the process in an informed consideration of options and trade-offs (TSP and Policy Labs are useful at this point). Importantly, you involve key people to make things happen with more people in order to enrich the vision of possible futures and legitimacy of the choices made to implement this vision.

Experiments in participatory and deliberative democracy, creativity, and collective intelligence show that high-quality deliberation requires at least the following seven ingredients:

Participants should be engaged through a “T-shaped” approach that combines deep technical expertise with a wide range of user perspectives.
Relevant public authorities should be closely involved and make a clear commitment as to how they treat the outputs of the process. The higher up they go on Sherry Arnstein’s participation ladder, the more likely they are to generate interest and a positive outcome.
Participants need to be given access to reasonably accurate information that they believe to be relevant to the issue.
Participants should represent the diversity of positions in the public. The benefits of cognitive diversity and the legitimacy of the process are best ensured by a sufficiently large — and, if possible, truly representative — sample of a given population.
Arguments offered by one side should be answered by considerations offered by those who hold other perspectives.
Participants should be allowed to sincerely weigh the merits of the arguments, and arguments offered by all participants should be considered on the merits, regardless of which participants offer them.
The process should be transparent, through the media and on- and offline interaction with a wider public, in order to increase the legitimacy of the solutions proposed and to tap into wider cognitive diversity.

At AI SF, Mehdi Miremadi from McKinsey Global Institute corroborated in “Have we reached peak human? The impact of AI on the workforce”:

economic futures look bleak when based on current trends in labor supply
“productivity growth” over the past five decades was based on large numbers of people entering the workforce
our ability to automate (up to 30% of many jobs) is how the story of AI will unfold

To wit, advanced analytics have near-term potential to unlock $11–13T in the economy (~15% of global GDP), with deep learning accounting for ~40%. Historical analogies exist, e.g., the era of early PC adoption created jobs despite dire warnings to the contrary.

At AI SF, Danny Lange presented how to train puppies: “On the road to artificial general intelligence” — game simulations Unity3D plus reinforcement learning used to train virtual puppies to play “fetch” and other skills. Building on this, Danny described several forms of learning inspired by biology, which go beyond deep learning. He showed examples of virtual puppies for:

Imitation Learning: e.g., see https://bit.ly/2zvYH51 (start 0:15)
Curriculum Learning: start with an easy problem, then make learning challenges progressively harder
Curiosity-driven Exploration: gets beyond problems which random exploration would never reach, i.e., agents don’t get stuck in a room (saddle points) because they want to explore other rooms

Youtube is failing its creators

This phenomenon is an indicator of broader future-of-work issues. If more people are making their primary income from distributed micro-work style projects, where does income security come from?

- Vlad Savov has written an excellent reflection on our relationship with iPhones.

We are cyborgs.

Azeem’s end note

I am spending a bit of time over the coming months thinking about data in the context of the new information age. I’m particularly curious about the full spectrum of issues from what personal rights around data usage should be, how those rights should be expressed and protected, especially in the context of derived attributes or characteristics the emerge from aggregated or population level data. I’m curious about collective data institutions like data exchanges, data trusts and data commons. I wonder about how business strategies might evolve beyond data network effects. And I’m intrigued by how data might be used in political & deliberative processes. And I want to understand better how we describe and unleash the economic value of data.

Education is delivery; learning is discovery.

Apple Executive John Couch on Rewiring Education (from the Getting Smart podcast):

Getting Smart Podcast: 164 - Apple Executive, John Couch, on Rewiring Education

During the application stage, the intrapreneur fulfills 10 questions from an online file, and based on this file, we select some of them for what we call pre-coaching, where we help them to enrich their application. Basically we work with them on two aspects:

One is to help them to move from the solution to the user problem: identify who is their target, and how painful is the problem for the target;
And second element, we connect them with other entities within Orange. Orange is a huge company (150,000 employees over 30 countries), and very often there are people working on a similar aspect of the intrapreneur project or people who could be interested in commercializing, distributing the intrapreneurs idea. So we connect people and sometimes it’s a match, sometimes it doesn’t match, but it’s another way to make the application progress;

We start very often with online coaching where we connect by phone, and we exchange on the project: we share with them some contacts, and they make the appointments, meet the people, and enrich the project. For us it’s a very important way to test if the intrapreneur is able to be self-starter, to take initiative, and to iterate on his project . Iteration is really a key skill for the intrapreneur;
Besides, each intrapreneur has to find out a business unit sponsor for his project: this networking is a fine way to meet this sponsoring demand;
When the project goes to Qualification, and then to Incubation, he usually keeps the same coach.

Evan Burton is a UX Designer, Usability Engineer, Data Science Enthusiast, finishing a master’s degree in Usability Engineering.
He’s currently writing his masters thesis on corporate intrapreneurship and innovation, with a focus on corporate acceleration and incubation, and how to best support intrapreneurs in the process of defining and developing their ideas into products or services for their company.

Evan claims that ‘one of his core research findings was that the role of coaching in these programs is very impactful. Research shows that coaches serve not only as an experienced guide, helping intrapreneurs to embrace a new way of working, but also as a crucial link to a network of experienced professionals both inside and outside the corporation. ’

”Certain central themes spring up repeatedly in cyberpunk. The theme of body invasion: prosthetic limbs, implanted circuitry, cosmetic surgery, genetic alteration. The even more powerful theme of mind invasion: brain-computer interfaces, artificial intelligence, neurochemistry – techniques radically redefining the nature of humanity, the nature of the self.

the research process is somewhat similar, from what I have experienced. The three main steps in the data science process are:

data sourcing—more than mere access, it’s also about understanding lineage and assessing quality and coverage;
data transformation—from filtering and simple arithmetic transformations to complex abductions like predictions and unsupervised clustering; and
results delivery—both socially and programmatically (i.e., as lines of code).

Whitney Phillips, an assistant professor of communication, culture, and digital technologies at Syracuse University, said that “the takeaway for establishment journalists is stark, and starkly distressing: just by showing up for work and doing their jobs as assigned, journalists covering the far-right fringe… played directly into these groups’ public relations interests. In the process, this coverage added not just oxygen, but rocket fuel to an already-smoldering fire.”

In an article in The Guardian, boyd and her colleague Joan Donovan discuss how hate groups throughout history not only sought the amplification of the media, but considered it one of their most essential recruitment tactics. In the 1969 autobiography of George Lincoln Rockwell, the founder of the American Nazi Party, he noted that “only by forcing the Jews to spread our message with their facilities could we have any hope of success in counteracting their left-wing, racemixing propaganda!”

The KKK — and many more groups of its ilk — have regularly used inflammatory rhetoric and behavior to bait journalists into giving them free press that would attract more people to their cause, both now and in history.

[…]

In response, many in the black, Jewish, and Catholic press promoted the idea of “dignified silence” or “selective silence,” or denying the hate group the oxygen that it so desperately wanted.

Who doesn’t want to think that the truth will always win in the end, that information not only wants to be free, but that this freedom will lead us toward a more just world — especially when it is your job to share information?

But in our current moment, it is a dangerously naïve idea. While the internet has led to the promotion of important voices we might not have otherwise heard, the last decade has demonstrated with searing clarity that this idea has far more powerfully to the amplification of lies, manipulation, and an epistemological collapse that has deformed human discourse and undermined the very notion of truth.

Norman said for people who want to take steps to reconciliation, the acknowledgement should lead to more questions about who the people listed in the acknowledgement are and how their land came to be possessed by settlers.

“It also needs to be personal,” she said. “We have to ask, ‘How am I benefitting by living on this land that is a traditional territory of Indigenous people?’”

“When we talk about the newness of territorial acknowledgements, these aren’t new. Acknowledging relationships to space and place is an ancient Indigenous practice that flows into the future,” said Recollet.

“What we see as concrete, what we see as the CN tower, as buildings, these are all places that have been prayed for, that have been gathering places for ceremonies and I think it is important to remember that.”

Asked to choose from a list of 15 different options which ones they thought impact on a student’s ability to thrive at university, almost nine in 10 (89 per cent) of university admissions officers cited “not being able to think and learn independently”.

This was followed by “unable to manage their own time or workloads” (88 per cent). Seven in 10 suggested that students do not appreciate what their course will involve, while 52 per cent felt they were “unable to carry out extended writing”; and the same number “unable to remember facts, possessing a ‘Google It’ mentality”.

And yet we persist in doing idiot things that can only possibly have this result:

Assessing school-teachers on the improvement their kids show in tests between the start and end of the year (which obviously results in their doing all they can depress the start-of-year tests).
Assessing researchers by the number of their papers (which can only result in slicing into minimal publishable units).
Assessing them — heaven help us — on the impact factors of the journals their papers appear in (which feeds the brand-name fetish that is crippling scholarly communication).
Assessing researchers on whether their experiments are “successful”, i.e. whether they find statistically significant results (which inevitably results in p-hacking and HARKing).

”In universities, this requires a rebalancing from the current emphasis on research to teaching. (A dean at one of Ontario’s more highly ranked universities told me recently that virtually every day there is a request to grant teaching release to a professor, yet no one has ever asked for release from research.)” — http://blog-en.heqco.ca/2017/07/harvey-p-weingarten-the-evolution-of-learning-outcomes-now-comes-the-exciting-part/

Here is one thing I gained from this Analysis. At times we encounter ‘a Code problem’ partly caused by ′ a workflow problem’ and partly caused by ‘a Design problem’ .

We may do a CODE patch fix for time being (ex. production bug), but having it documented as ‘40% Workflow problem, 60% Design problem’ will help to consolidate all these ‘contributing percentages’ to come up with permanent fixes at a Later time.

innovation doesn’t happen in isolation.

Great ideas come alive when groups of passionate people come together to inspire, support and collaborate. From Stockholm and Tel Aviv to Seoul and Berlin, and of course, Silicon Valley — we have seen, time and time again, the benefits that such rich ecosystems bring entrepreneurs.

YOU ARE NOT SAFE

I, Ryan Ray, released the MacMillan Utility source code. I acted alone. No one helped me, and no one told me to do it. I did this because ‘security’ is a myth. Contrary to what you might have heard, my friends, you are not safe.

Safety is a story. It’s something we teach our children so they can sleep at night, but we know it’s not real.

Beware, baffled humans. Beware of false prophets who will sell you a fake future, of bad teachers, corrupt leaders and dirty corporations. Beware of cops and robbers… the kind that rob your dreams. But most of all, beware of each other, because everything’s about to change.

The world is going to crack wide open. There’s something on the horizon. A massive connectivity. The barriers between us will disappear, and we’re not ready.

We’ll hurt each other in new ways. We’ll sell and be sold. We’ll expose our most tender selves, only to be mocked and destroyed. We’ll be so vulnerable, and we’ll pay the price. We won’t be able to pretend that we can protect ourselves anymore.

It’s a huge danger, a gigantic risk, but it’s worth it. If only we can learn to take care of each other. Then this awesome, destructive new connection won’t isolate us. It won’t leave us in the end so… totally alone.

When designers center around the user, where do the needs and desires of the other actors in the system go? The lens of the user obscures the view of the ecosystems it affects.

’[…] The experience for a Sprig customer is super convenient, almost magical; the experience for a chef or courier…? We don’t know. We don’t get to know. We’re just here to press the button.’

For users, this is what it means to be at the center: to be unaware of anything outside it. User-Centric Design means obscuring more than it surfaces.

Twitter is a powerful publishing platform that has become the de facto official medium for famous people to make public statements about what is going on right now.

The problem is, that’s not the description of a social network. It’s a description of a publishing platform. Twitter’s trouble is that it’s being viewed by investors as a social network.

John Gruber of Daring Fireball.

Cogent.

Warren Buffett manages to entertain and inform in his 2015 letter to shareholders.

(This quote comes from Mr. Buffett’s discussion on the unpredictable but beneficial technologies that come from market-driven innovation.)

Loren Grush writing for The Verge on the potential impact of the Laser Interferometer Gravitational-Wave Observatory (LIGO)’s gravitational wave discovery on research and innovation in science.

It’s the simple things in writing.

Umair Haque on one of the modern Web’s most important problems.

I could’ve quoted many other sentences from this article. Great points, as always — and powerful parallels with Seth Godin’s The Icarus Deception.

The residential university she hopes to create would differ radically from what’s been done traditionally. Project-based learning is the cornerstone of her vision.

“I’m looking at a new model, where the whole sort of vocabulary is different,” she said. “The distinction between undergrad and grad goes away.”

Dean for graduate education to take leave, start new university

So neat. I hope this project gets off the ground — the distinction between different levels of study in the post-secondary universe needs to be tested in the 21st century.

Your generation will set goals for what you want to become – like an engineer, health worker, writer or community leader. You’ll have technology that understands how you learn best and where you need to focus. You’ll advance quickly in subjects that interest you most, and get as much help as you need in your most challenging areas. You’ll explore topics that aren’t even offered in schools today. Your teachers will also have better tools and data to help you achieve your goals.

Even better, students around the world will be able to use personalized learning tools over the internet, even if they don’t live near good schools. Of course it will take more than technology to give everyone a fair start in life, but personalized learning can be one scalable way to give all children a better education and more equal opportunity.

It’ll be a while before they can read it, but the newborn Chan Zuckerberg child seems to be in pretty great hands.

Also: it’s worth pairing this optimistic worldview with Umair Haque’s critique of it.

”[John F. Kennedy’s] challenge disturbed the National Aeronautics and Space Administration’s original plan for a stepped, multi-generational strategy: Wernher von Braun, NASA’s chief of rocketry, had thought the agency would first send men into Earth’s orbit, then build a space station, then fly to the moon, then build a lunar colony. A century hence, perhaps, humans would travel to Mars. Kennedy’s goal was also absurdly ambitious. A few weeks before his speech, NASA had strapped an astronaut into a tiny capsule atop a converted military rocket and shot him into space on a ballistic trajectory, as if he were a circus clown; but no American had orbited the planet. The agency didn’t really know if what the president asked could be done in the time he allowed, but it accepted the call.”

This required the greatest peacetime mobilization in the nation’s history.

The (further) verification that spooky physics has important implications for cryptography.

From http://www.economist.com/news/science-and-technology/21676733-one-weirdest-bits-physics-proved-beyond-doubt-almost-hidden-no-more

A profound change is sweeping across the entrepreneurial landscape. In the quest to improve lives or preserve the earth’s natural resources, today’s top minds are not only coming up with game-changing products and services. They are also reinventing systems and harnessing diverse tools — from cross-sector partnerships to capital markets — to meet their goals. Many of these innovative thinkers are young, coming of age in the aftermath of Sept. 11, amid the destruction of two protracted wars and the economic uncertainties ushered in by the Great Recession. They are digital experts, who, thanks to social media, smartphones and access to limitless information, have grown up with a sense of global community that transcends geographic boundaries. And they seem to have social consciousness embedded in their DNA. They are united in wanting to do more than acquire material riches. They measure success by their ability to transform the lives of others. Their question is not ‘’What do I want to be when I grow up?‘’ but ‘’How will the world be different because I lived in it?‘’

As a result, financial success and social impact are becoming ever more linked, with the lines blurring between the business and nonprofit sectors. Twenty years ago, businesses, nonprofits and government made up three distinct parts of society, with their own responsibilities, goals and strategies. In the 1990s, the conversation started to move from how to create the right organizations and programs to which approaches could — with different sectors working together — help solve some of the world’s most profound social problems. In the past couple of decades, there’s been a remarkable acceleration in the overlap between these different sectors.

What is unfolding is a blending of the goals and business models for traditional for-profit enterprises and nonprofit organizations. In the process, nonprofits with empathy-based, revenue-generating models have emerged at the same time as C.E.O.s and entrepreneurs who want to build companies that generate social value through their products and services.

From Laura Arrillaga-Andreessen’s New York Times article on new social entrepreneurs.

The article oddly lumps AirBnB and Palantir in with three other more definitively social enterprises, and not all of the founders profiled are as young as the initial first few paragraphs make them seem. Still, it’s an inspiring group of people to read about.

James Greyson on “precycling”. An interesting concept — how have the products we use been prepared to be wasted? It strikes me that most products are designed with their use in mind, but rarely is the entire product lifecycle part of the design discussion.

Greyson published a paper on precycling insurance as an economic mechanism to facilitate this behaviour.

The data mindset is good for some questions, but completely inadequate for others. But try arguing that with someone who insists on seeing the numbers.

The promise is that enough data will give you insight. Retain data indefinitely, maybe waterboard it a little, and it will spill all its secrets.

There’s a little bit of a con going on here. On the data side, they tell you to collect all the data you can, because they have magic algorithms to help you make sense of it.

On the algorithms side, where I live, they tell us not to worry too much about our models, because they have magical data. We can train on it without caring how the process works.

The data collectors put their faith in the algorithms, and the programmers put their faith in the data.

At no point in this process is there any understanding, or wisdom. There’s not even domain knowledge. Data science is the universal answer, no matter the question.

In a world where everything is tracked and kept forever, like the world we’re for some reason building, you become hostage to the worst thing you’ve ever done.

Whoever controls that data has power over you, whether or not they exercise it. And yet we treat this data with the utmost carelessness, as if it held no power at all.

Eric Schmidt of Google suggests that one way to solve the problem is to never do anything that you don’t want made public. But sometimes there’s no way to know ahead of time what is going to be bad.

In the forties, the Soviet Union was our ally. We were fighting Hitler together! It was fashionable in Hollywood to hang out with Communists and progressives and other lefty types.

Ten years later, any hint of Communist ties could put you on a blacklist and end your career. Some people went to jail for it. Imagine if we had had Instagram back then.

A more recent and less fictitious example is electronic logging devices on trucks. These are intended to limit the hours people drive, but what do you do if you’re caught ten miles from a motel?

The device logs only once a minute, so if you accelerate to 45 mph, and then make sure to slow down under the 10 mph threshold right at the minute mark, you can go as far as you want.

So we have these tired truckers staring at their phones, bunny-hopping down the freeway late at night.

Of course there’s an obvious technical countermeasure. You can start measuring once a second.

Notice what you’re doing, though. Now you’re in an adversarial arms race with another human being that has nothing to do with measurement. It’s become an issue of control, agency and power.

You thought observing the driver’s behavior would get you closer to reality, but instead you’ve put another layer between you and what’s really going on.

These kinds of arms races are a symptom of data disease. We’ve seen them reach the point of absurdity in the online advertising industry, which unfortunately is also the economic cornerstone of the web. Advertisers have built a huge surveillance apparatus in the dream of perfect knowledge, only to find themselves in a hall of mirrors, where they can’t tell who is real and who is fake.

“Data disease”. What a term.

From Maciej Cegłowski’s talk at the Strata+Hadoop 2015 conference in NYC.

Kepler’s astronomers decided to found Planet Hunters, a program that asked “citizen scientists” to examine light patterns emitted by the stars, from the comfort of their own homes.

In 2011, several citizen scientists flagged one particular star as “interesting” and “bizarre.” The star was emitting a light pattern that looked stranger than any of the others Kepler was watching.

Acquiescence is a good word for this.

From http://blindspot.org.uk/second-policy-switch/

John Scalzi.

This makes me feel better. I’ve always thought I had to use Scrivener to be a serious writer. Phew.

Laszlo Bock, Google’s Head of People Operations, on how to manage Google’s talent.

Laszlo seems like a really really nice fella.

Sam Altman on the launch of Y Combinator’s new research lab.

This is noble but scary. It might provide an alternative to explicitly for-profit research in the face of decline in support for public research, but it is privatizing in its own right. This sort of effort might permit such decline even further…

Human prosperity, we are told, is an unalloyed perfect metal, forged in the crucible of the industrial revolution. The modern world was born in a revolution of steam and flame. Abundance, available endlessly in infinite quantities, poured forth from the workshops of creation. And now forevermore, thanks to the alchemical formula of technology, capital, and power, will the world get better.

Like all myths, our creation myth of abundance reveals the truth at the heart of the lie. The facts are these: the beggar’s prosperity of meta-modernity is not an unalloyed good, available endlessly in infinite abundance, forged nobly in a great and virtuous workshop. It was born in the rape of the earth, nurtured by war and holocaust, conceived in the workhouse and plantation. And it is ordered, today, by a creaking, buckling system of finance, barely contained volcanos of social upheaval, and armies of middle managers who desperately wish for better things to devote their one and only lives to than pillaging the earth and plundering the future in the noble quest for… new flavours of deodorant.

It is true that the world is getting better — in the narrowest of terms. But it is truer that it is precisely the unbridled pursuit of such a simplistic notion of progress which is, simultaneously, paradoxically, contradictorily, causing it to get worse in many real, and irreversible ways.

And so. It is confronting, untangling, and resolving exactly the paradoxes and contradictions of our Predator’s Bargain with prosperity that is the great challenge to which this generation of ours must rise. Not merely philosophically, but pragmatically, in the real world, here and now. Rise, or else surely fall from what little grace our forefathers earned for us.

Oh, wow.

Umair Haque.

An important argument for humility.

From the Cornell x Tulane study on overclaiming.

Figuring out how to live forever is expensive.

From Re/code’s story on Google’s partnership with Ancestry.com.

neurosciencestuff:

A group led by Assistant Professor Dan Ohtan Wang from Kyoto University’s Institute for Integrated Cell-Material Sciences (iCeMS) in Japan successfully visualized RNA behavior and its response to drugs within the living tissue brain of live mice by labeling specific RNA molecules with fluorescent probes. Their study, published in Nucleic Acids Research, can potentially lead to faster, and more accurate screening processes for the discovery and development of new drugs.

RNA is a molecule that plays a key role within a living organism, holding information as to when, where and how much protein must be allocated, which is also responsible for controlling the biological reactions within a living cell. RNAs behave uniquely and are distributed unequally in each cell, existing more in some areas of the cell than others depending on environmental factors and cell conditions. In some cases, these chemical changes can put the cell’s health at risk due to RNA disruption. However, it is unclear as to how the distribution of RNA molecules is regulated in the cell, and what causes them to act abnormally.

By introducing a non-toxic, fluorescent probe within the brain of live mice, the team succeeded in visualizing targeted RNA in the cell nucleus. This fluorescent probe emits varying intensities of light depending on RNA concentration levels enabling the team to effectively quantitatively analyze RNA in the living body. The imaging technique, for the first time in the world, quantitatively conveyed that the RNA behavior in live tissue differed from that of a cultured cell when a drug was administered.

Wang hopes that this new imaging technique can help reveal “the natural state of RNA,” that allows us to observe the emergence and disappearance of RNA clusters in many types of species, including those that cannot be genetically engineered. “Our next goal is to investigate differences of RNA activity in a live, single cell, what regulates RNA activity, and compare healthy tissue and unhealthy tissue to elucidate gene expression mechanisms and pathologies caused by abnormal RNA activity.”

“No one ever gave me a reason why they didn’t want the hologram to appear,” said Craze Fest promoter Malcolm Jones. “They didn’t have a real reason. They believed that it would start trouble, but the first thing Chief Keef said via hologram was: ’Chicago, we need to stop the violence. Let our kids live.’”

Why is an authority making decisions based on what he’d “heard” about someone, especially when he “knows nothing” about the person? Isn’t that essentially stereotyping, if not racism?

From Police shut down show by Chief Keef’s hologram by Sam Byford on The Verge.

Paul Saffo’s approach to forecasting.

Also, reading about Paul Saffo brought me to the Long Now Foundation — so neat!

Mike Monteiro, “Why you need design”. (https://medium.com/@monteiro/why-you-need-design-77dce41e0e0c)

A little weird and very clever.

Mike Monteiro, “Why you need design”. (Again: https://medium.com/@monteiro/why-you-need-design-77dce41e0e0c)

I’m really interested in this “dichotomy”. I like Mike’s emphasis on the non-art of design: to him, it is a practice.

“A good designer behaves like a skilled professional with analytical, persuasive, creative, and social skills. You can count on them to solve problems, present good work in a timely manner, be accountable, and argue from an informed point of view.” - Mike Monteiro

And I agree with him wholeheartedly. Yet, working with artists and contemporary art at Eastern Edge over the last few weeks has led me to a great appreciation of contemporary art, and the capacity of art to do… well… something.

I guess that’s sometimes the point: art doesn’t necessarily achieve an intentional goal. Design does. Or rather, it should.

[Contemporary] Art can be designed.

However, art can be designed. But can design be contemporary art? What would that mean?

Off-the-cuff, it would mean that the design pushes contemporary boundaries. It would make you think about something you hadn’t thought you’d think about. Or, it would make you feel something you hadn’t felt before. Or that you feel a lot.

However, design still can’t be self-expression. By definition, it is intentionally the expression of something else—the expression of a solution to a problem, perhaps. Design can be art, but it shouldn’t necessarily try to be.

(Aside: I’m reminded of instantiation validity. A design is a version of a solution to a problem, but if it fails, we should remember that a design is distinct from the theoretical solution, and that the design can fail separate from the solution itself. This is convoluted, but it means we can try the same solution with a different design.)

Get a rat and put it in a cage and give it two water bottles. One is just water, and one is water laced with either heroin or cocaine. If you do that, the rat will almost always prefer the drugged water and almost always kill itself very quickly, right, within a couple of weeks. So there you go. It’s our theory of addiction.

Bruce comes along in the ’70s and said, “Well, hang on a minute. We’re putting the rat in an empty cage. It’s got nothing to do. Let’s try this a little bit differently.” So Bruce built Rat Park, and Rat Park is like heaven for rats. Everything your rat about town could want, it’s got in Rat Park. It’s got lovely food. It’s got sex. It’s got loads of other rats to be friends with. It’s got loads of colored balls. Everything your rat could want. And they’ve got both the water bottles. They’ve got the drugged water and the normal water. But here’s the fascinating thing. In Rat Park, they don’t like the drugged water. They hardly use any of it. None of them ever overdose. None of them ever use in a way that looks like compulsion or addiction. There’s a really interesting human example I’ll tell you about in a minute, but what Bruce says is that shows that both the right-wing and left-wing theories of addiction are wrong. So the right-wing theory is it’s a moral failing, you’re a hedonist, you party too hard. The left-wing theory is it takes you over, your brain is hijacked. Bruce says it’s not your morality, it’s not your brain; it’s your cage. Addiction is largely an adaptation to your environment.

[…]

We’ve created a society where significant numbers of our fellow citizens cannot bear to be present in their lives without being drugged, right? We’ve created a hyperconsumerist, hyperindividualist, isolated world that is, for a lot of people, much more like that first cage than it is like the bonded, connected cages that we need.

The opposite of addiction is not sobriety. The opposite of addiction is connection. And our whole society, the engine of our society, is geared towards making us connect with things. If you are not a good consumer capitalist citizen, if you’re spending your time bonding with the people around you and not buying stuff—in fact, we are trained from a very young age to focus our hopes and our dreams and our ambitions on things we can buy and consume. And drug addiction is really a subset of that.

Johann Hari, Does Capitalism Drive Drug Addiction? (via bigfatsun).

Hm. A brief skim of some of the research done on Bruce Alexander’s “Rat Park” in the last few decades and the Wikipedia article on the subject seems to indicate that the conclusion drawn here isn’t as straightforward as we’d like, but overall, it looks like this subject should be studied more. Disappointing that the SFU studies ran out of funding.

Still, it’s an interesting thought, and an important contrast to prevailing views on addiction (as Johann Hari suggests).

- @umairh (http://twitter.com/umairh/status/618463980391145472).

Different scope, too – a biased algorithm can scale quite a bit more and quite a bit faster than a biased person.

Aside: isn’t a bias arguably an algorithm anyway? Bias as behavioural algorithm leads to a lack of design foresight which then leads to institutional bias in programmed algorithms. Hm.